1. Combinatorial Analysis: Rules of sum and product, permutations, arrangements and combinations. Probability Theory:Sample space and events, axioms and theorems of probability. Independent events, conditional and total probability, Bayes’ theorem. 

2. Random Variables: Basic concepts, probability mass and density functions, distribution function, mean, variance, standard deviation, basic discrete and continuousdistributions. 

3. Descriptive Statistics: Frequency distributions and histograms, data summary and display.

4. Point estimation, statistical intervals of means, variances and proportions. Tests of hypotheses.